Power consumption estimation using in-memory database computation
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Date
2016
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Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Open Access Color
Green Open Access
Yes
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Abstract
In order to efficiently predict electricity consumption, we need to improve both the speed and the reliability of computational environment. Concerning the speed, we use in-memory database, which is taught to be the best solution that allows manipulating data many times faster than the hard disk. © 2016 IEEE.
Description
Keywords
In-Memory Database, Machine Learning, Power Consumption, Machine Learning, Power Consumption, In-Memory Database
Turkish CoHE Thesis Center URL
Fields of Science
0502 economics and business, 05 social sciences, 0101 mathematics, 01 natural sciences
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13th HONET-ICT International Symposium on Smart MicroGrids for Sustainable Energy Sources Enabled by Photonics and IoT Sensors, HONET-ICT 2016 -- 13th HONET-ICT International Symposium on Smart MicroGrids for Sustainable Energy Sources Enabled by Photonics and IoT Sensors, HONET-ICT 2016 -- 13 October 2016 through 14 October 2016 -- Haspolat, Nicosia -- 125073
Volume
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Start Page
164
End Page
169
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